docs: def _parallel_predict_proba(estimators, estimators_features, X, n_classes, combination, estimators_weight):
      """Private function used to compute (proba-)predictions within a job."""
      n_samples = X.shape[0]
      proba = np.zeros((n_samples, n_classes))
  
      for estimator, features, weight in zip(estimators, estimators_features, estimators_weight):
          proba_estimator = estimator.predict_proba(X[:, features])
          if combination in ['weighted_voting', 'weighted_bmr']:
              proba += proba_estimator * weight
          else:
              proba += proba_estimator
  
      return proba